Abstract: A method (100) for creating a model for positioning, the method (100) comprising: receiving (S150) a training dataset (1) comprising samples (10) of an estimation labeled type, each sample (10) of the estimation labeled type being associated with a measurement position, each sample (10) of the estimation labeled type comprising sensor data (12), measured at the measurement position associated with the sample (10), the sensor data (12) being characteristic of the measurement position associated with the sample (10); an estimated measurement position (14), being an estimate of the measurement position associated with the sample (10); an estimated accuracy (16), being an estimate of an accuracy of the estimated measurement position (14); training (S160) a machine learning model (20) to convert sensor data (12) to a position, wherein the training is based on the samples (10) of the estimation labeled type in the training dataset (1), whereby the model for positioning is created.

Abstract: A method for generating an indoor environment model of a building. The method comprises forming a transmitter location model for defining positions of transmitters in said building using gathered information for establishing transmitter locations. The method further comprises receiving signal strength indicative measurements determined for a number of transmitters using at least one electronic communications device wherein the signal strength indicative measurements are based on a signal which has varying signal propagation characteristics in the indoor environment The signal strength indicative measurements are acquired from a number of known locations in the building, identifying discrepancies of signal transmittance in said indoor environment based on said signal strength indicative measurements in relation to said transmitter location model.

Abstract: A method in a movable device for locating or positioning of the movable device within an environment comprises: receiving, from an external unit, a central environment model; determining distance-dependent measurements for one or more positions of the movable device; determining a location of the movable device based on the received central environment model and the determined distance-dependent measurements, said determining comprising: forming a local environment model defining estimated locations of the wireless transmission sources and of the one or more positions of the movable device, wherein the estimated locations of the wireless transmission sources in the local environment model are updated in relation to the central environment model, wherein the updated estimated locations of the wireless transmission sources and the estimated locations of the one or more positions of the movable device are set based on a calculated error of the local environment model in relation to the determined distance-depend

Abstract: A method for estimating accuracy of a position determination based on distance-dependent measurements is disclosed. The method comprises: storing area information in relation to pre-defined geographical areas, wherein the area information for each pre-defined geographical area includes accuracy information relating to accuracy of position determinations based on distance-dependent measurements in the pre-defined geographical area; receiving a request for an accuracy estimate; determining an area affiliation based on received position information in said request, wherein the area affiliation defines at least one applicable geographical area among the pre-defined geographical areas, wherein the position of the receiving unit is located within the at least one applicable geographical area; and determining the accuracy estimate based on the stored area information for the at least one applicable geographical area.

Abstract: A method for generating a model of an environment enabling positioning within the environment is disclosed.

Abstract: A method for generating a model of an environment enabling positioning within the environment is disclosed.